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Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach

Artificial Intelligence: A Modern Approach

Product ID : 19308675
4.1 out of 5 stars


Galleon Product ID 19308675
UPC / ISBN 0131038052
Shipping Weight 3.6 lbs
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Binding: Hardcover
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Model
Manufacturer Prentice Hall
Shipping Dimension 9.29 x 7.48 x 1.61 inches
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Edition 1st
Number Of Pages 960
Publication Date 1995-02
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About Artificial Intelligence: A Modern Approach

Product Description A highly accessible, up-to-date professional reference for programmers, software engineers, system administrators, or technical managers, this book integrates state-of-the-art AI techniques into intelligent agent designs using examples and exercises to lead the reader from simple reactive agents to full knowledge-based agents with natural language capabilities. Amazon.com Review Artificial Intelligence: A Modern Approach introduces basic ideas in artificial intelligence from the perspective of building intelligent agents, which the authors define as "anything that can be viewed as perceiving its environment through sensors and acting upon the environment through effectors." This textbook is up-to-date and is organized using the latest principles of good textbook design. It includes historical notes at the end of every chapter, exercises, margin notes, a bibliography, and a competent index. Artificial Intelligence: A Modern Approach covers a wide array of material, including first-order logic, game playing, knowledge representation, planning, and reinforcement learning. From the Publisher The most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. From the Back Cover Integrates state-of-the-art AI techniques into intelligent agent designs, using examples and exercises to lead the reader from simple reactive agents to full knowledge-based agents with natural language capabilities. Covers areas that are sometimes under-emphasized--reasoning under uncertainty, learning, natural language, vision and robotics--and explains in detail some of the more recent ideas in the field e.g., simulated annealing, memory-bounded search, global ontologies, dynamic belief networks, neural nets, inductive logic, programming, computational learning theory, and reinforcement learning. This highly accessible and well-written, state-of-the-art professional reference is for programmers, software engineers, system administrators, or technical managers who want to learn about or use A.I. techniques and software solutions.